38 citations · 86 across the 19 of their papers we have counts for
4 papers · 1 filter
Differentiating Metropolis-Hastings to Optimize Intractable Densities
Gaurav Arya, Ruben Seyer, Frank Schäfer +7
We develop an algorithm for automatic differentiation of Metropolis-Hastings samplers, allowing us to differentiate through probabilistic inference, even if the model has discrete…
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought
Lionel Wong, Gabriel Grand, Alexander K. Lew +4
How does language inform our downstream thinking? In particular, how do humans make meaning from language--and how can we leverage a theory of linguistic meaning to build machines…
Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs
Alexander K. Lew, Tan Zhi-Xuan, Gabriel Grand +1
Even after fine-tuning and reinforcement learning, large language models (LLMs) can be difficult, if not impossible, to control reliably with prompts alone. We propose a new infere…
PAP Spaces: Reasoning Denotationally About Higher-Order, Recursive Probabilistic and Differentiable Programs
Mathieu Huot, Alexander K. Lew, Vikash K. Mansinghka +1
We introduce a new setting, the category of PAP spaces, for reasoning denotationally about expressive differentiable and probabilistic programming languages. Our semantics is ge…